Manager, Data Science & AI/ML - Credit Risk & Lending

About the position Responsibilities

• Lead cross-functional initiatives to deliver impactful machine learning solutions that enhance member experiences, with a focus on credit and lending products.
• Manage and inspire a talented team, driving the development of innovative credit insights and risk assessment solutions that impact millions of customers.
• Oversee the end-to-end development and deployment of advanced machine learning models to improve the accuracy, fairness, and inclusivity of credit assessments.
• Collaborate with Legal and compliance in regards to fair lending practices and model governance.
• Play a key role in shaping the credit team's strategic direction and ensuring alignment with Chime's broader business goals.
• Leverage transactional and financial data to improve access to capital for loan applicants and enhance member financial security.
• Champion a data-driven approach to decision-making across the organization.
• Make critical long-term decisions regarding machine learning processes and best practices.
• Collaborate with product managers, engineering, and other stakeholders to shape the product roadmap and define project goals.
• Directly contribute to Chime's success by delivering data science solutions that improve both customer satisfaction and business outcomes.

Requirements

• 7+ years of industry experience developing machine learning models for credit risk products from inception to production, with a proven ability to tailor solutions to real-world business challenges in a cross-functional environment.
• 5+ years of managerial experience in data science and machine learning, with a track record of leading teams to deliver impactful solutions.
• Strong expertise in credit and lending risk assessment, with experience building and deploying models that meet regulatory requirements with respect to model governance and fair lending.
• Deep understanding of modern AI/ML techniques, including classification, clustering, optimization, deep learning, and natural language processing.
• Excellent product intuition and a passion for working iteratively in a fast-paced environment.
• M.S. or Ph.D. in Machine Learning or a related STEM field, with hands-on experience building production ML pipelines, from development to deployment, at scale.
• Proficiency in Python and intermediate to advanced knowledge of SQL, with the ability to wrangle data from diverse sources.
• Experience with technologies such as AWS, Kafka, Airflow, Redis, MySQL, Postgres, Spark, Snowflake, and Looker.
• Exceptional communication and collaboration skills, with experience working with stakeholders across product, design, engineering, and marketing.

Benefits

• A thoughtful hybrid work policy that combines in-office days and trips to team and company-wide events depending on location to ensure you stay connected to your work and teammates, whether you're local to one of our offices or remote.
• Hybrid work perks like backup child, elder and/or pet care, as well as a subsidized commuter benefit.
• Competitive salary based on experience.
• 401k match plus great medical, dental, vision, life, and disability benefits.
• Generous vacation policy and company-wide Chime Days, bonus company-wide paid days off.
• 1% of your time off to support local community organizations of your choice.
• Annual wellness stipend to use towards eligible wellness related expenses.
• Up to 24 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents.
• Access to Maven, a family planning tool, with $15k lifetime reimbursement for egg freezing, fertility treatments, adoption, and more.
• In-person and virtual events to connect with your fellow Chimers-think cooking classes, guided meditations, music festivals, mixology classes, paint nights, etc., and delicious snack boxes, too!
• A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress. Apply tot his job Apply To this Job

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